关于弱半素理想的一些研究

主要给出了弱半素理想的一些性质,证明了弱半素环的中心是约化环.     

Evaluation of humic acid removal by a flat submerged membrane photoreactor

A flat submerged membrane combined with a TiO 2 /UV photocatalytic reactor (FSMPR) was employed in batch mode to remove humic acid (HA). HA removal efficiency was characterized by UV 254 absorbance, UV-vis spectra, dissolved organic carbon (DOC) concentration, specific UV absorbance (SUVA), and trihalomethane formation potential (THMFP). The FSMPR process was effective in removing more than 86% of DOC and nearly 100% of UV 254 absorbance, while the THMFPs of samples were reduced to < 19 μ g/L after 150 min of treatment. In addition, changes in transmembrane pressure (TMP) with and without UV were evaluated; TiO 2 /UV was effective at controlling membrane fouling by HA. Analysis of the molecular weight (MW) distributions and three-dimensional excitation-emission matrix (EEM) fluorescence spectra of HAs revealed that the effectiveness in membrane fouling control is a result of changes in HA molecular characteristics. The TiO 2 /UV photocatalytic reactor caused the degradation of high MW, hydrophobic humic-like molecules to low MW, hydrophilic protein-like molecules, although this fraction was not completely removed during 150 min of treatment and was less responsible for membrane fouling.     

基于RFID技术的电子围栏内施工人员行为预判与告警算法

在电子围栏内施工人员行为预判与告警研究中,面对不确定的行为信息,常见的告警算法存在大量时隙分配冲突,导致算法的自适应性较差。为此,提出基于射频识别(Radio Frequency Identification, RFID)技术的电子围栏内施工人员行为预判与告警算法。通过远程通信和RFID读写器实时读取施工人员的位置信息和行为信息,将逻辑运算符与时间约束运算符相结合预判施工人员行为,在预判到危险行为后,产生相应的告警信息,设计防冲突算法,将告警信息传递到对应的电子标签上,实现对施工人员的告警。实验结果表明：面对不确定的行为信息,设计的告警算法对施工人员行为信息识别水平高,在时隙分配中未发生冲突事件,且分配成功率在99%以上,其自适应性得到提升。     

A20 (TNFAIP3) deficiency in myeloid cells triggers erosive polyarthritis resembling rheumatoid arthritis

A20 (TNFAIP3) is a protein that is involved in the negative feedback regulation of NF-κB signaling in response to specific proinflammatory stimuli in different cell types and has been suggested as a susceptibility gene for rheumatoid arthritis. To define the contribution of A20 to rheumatoid arthritis pathology, we generated myeloid-specific A20-deficient mice and show that specific ablation of Tnfaip3 in myeloid cells results in spontaneous development of a severe destructive polyarthritis with many features of rheumatoid arthritis. Myeloid-A20-deficient mice have high levels of inflammatory cytokines in their serum, consistent with a sustained NF-κB activation and higher TNF production by macrophages. Destructive polyarthritis in myeloid A20 knockout mice was TLR4-MyD88 and IL-6 dependent but was TNF independent. Myeloid A20 deficiency also promoted osteoclastogenesis in mice. Together, these observations indicate a critical and cell-specific function for A20 in the etiology of rheumatoid arthritis, supporting the idea of developing A20 modulatory drugs as cell-targeted therapies.     

特厚煤层综放工作面采运系统的可靠性模型与优化

分析了马道头煤矿特厚煤层综放工作面采运系统结构组成,利用设备有效度公式建立采运系统可靠性数学模型,通过观测数据计算系统及单元设备的有效度,确定影响生产效率薄弱环节,并总结系统设备发生故障的原因,提出了工作面采运系统优化方案。     

Mining potential social relationship with active learning in LBSN

Rapid development of local-based social network ( LBSN ) makes it more convenient for re-searchers to carry out studies related to social network.Mining potential social relationship in LBSN is the most important one.Traditionally, researchers use topological relation of social network or tel-ecommunication network to mine potential social relationship.But the effect is unsatisfactory as the network can not provide complete information of topological relation.In this work, a new model called PSRMAL is proposed for mining potential social relationships with LBSN.With the model, better performance is obtained and guaranteed, and experiments verify the effectiveness.     

基于趋势特征聚类的多元相似时间序列的提取

历史相似时间序列的提取在数据挖掘、工业故障检测以及故障根源分析等领域应用非常广泛。针对工业报警系统中异常根源分析方法存在的问题,提出了一种基于趋势特征聚类的多元相似时间序列的提取方法,可以有效地辅助现场工作人员分析关键变量发生异常变化的根源。首先对多元时间序列进行分段线性表示,获得变量的趋势特征信息;然后采用基于密度峰值聚类分析算法对获得的趋势特征在高维空间中聚类,从而实现历史数据的相似性提取;最后可根据关联变量的幅值变化量分析导致主变量发生异常变化的根源变量。数值仿真和实际工业数据案例验证了所提方法的有效性。     

Secure Two-Party Distance Computation Protocol Based on Privacy Homomorphism and Scalar Product in Wireless Sensor Networks

Numerous privacy-preserving issues have emerged along with the fast development of the Internet of Things. In addressing privacy protection problems in Wireless Sensor Networks(WSN), secure multi-party computation is considered vital, where obtaining the Euclidian distance between two nodes with no disclosure of either side’s secrets has become the focus of location-privacy-related applications. This paper proposes a novel Privacy-Preserving Scalar Product Protocol(PPSPP) for wireless sensor networks. Based on PPSPP, we then propose a Homomorphic-Encryption-based Euclidean Distance Protocol(HEEDP) without third parties. This protocol can achieve secure distance computation between two sensor nodes. Correctness proofs of PPSPP and HEEDP are provided, followed by security validation and analysis. Performance evaluations via comparisons among similar protocols demonstrate that HEEDP is superior; it is most efficient in terms of both communication and computation on a wide range of data types, especially in wireless sensor networks.     

鹿茸的组织结构及离体细胞的显微结构观察

本文对鹿茸的组织结构、鹿茸皮肤及顶端肉质部分的显微结构进行了较详尽的观察,同时对从鹿茸分离的细胞及由鹿茸组培养出的细胞形态结构也作了初步研究。     

滞后对象的连续模型参考自适应控制

本文基于MRAC的基本原理,提出了一种从模型取状态的滞后系统的MRAC方案。这种方法较之其它方案结构简单,且具有一定的抗输出端扰动的能力。仿真结果说明了系统结构是可行的。